AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Src-like-adapter 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9H6Q3

UPID:

SLAP2_HUMAN

Alternative names:

Modulator of antigen receptor signaling; Src-like adapter protein 2

Alternative UPACC:

Q9H6Q3; A8K648; E1P5U1; E1P5U2; Q5TH27; Q5TH28; Q8WY18; Q96QI4; Q9H135

Background:

Src-like-adapter 2, also known as Modulator of antigen receptor signaling, plays a crucial role in the immune system. It functions as an adapter protein that negatively regulates T-cell receptor (TCR) signaling, inhibiting T-cell antigen-receptor induced activation of nuclear factor of activated T-cells. This protein acts by linking signaling proteins such as ZAP70 with CBL, leading to a CBL dependent degradation of signaling proteins.

Therapeutic significance:

Understanding the role of Src-like-adapter 2 could open doors to potential therapeutic strategies.

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